code: def resolve_none(data):
      # replace None to '_'
      for sent_idx in range(len(data)):
          for tok_idx in range(len(data[sent_idx])):
              for feat_idx in range(len(data[sent_idx][tok_idx])):
                  if data[sent_idx][tok_idx][feat_idx] is None:
                      data[sent_idx][tok_idx][feat_idx] = "_"
      return data
  
imports: import random
  import logging
  import copy
  import torch
  from collections import namedtuple
  from torch.utils.data import DataLoader
  from torch.nn.utils.rnn import pad_sequence
  from stanza.models.common.bert_embedding import filter_data
  from stanza.models.common.data import map_to_ids, get_long_tensor, get_float_tensor, sort_all
  from stanza.models.common.vocab import PAD_ID, VOCAB_PREFIX, CharVocab
  from stanza.models.pos.vocab import WordVocab, XPOSVocab, FeatureVocab, MultiVocab
  from stanza.models.pos.xpos_vocab_factory import xpos_vocab_factory
  from stanza.models.common.doc import *
label_desc: Use image node_id 11 for calling the Dataset obj's underlying member method code with example usage: obj.resolve_none(data) and returns: data